Introduction to data visualization

MACS 40700
University of Chicago

March 27, 2017

Me

Course website

Course objectives

  • Understand how the human mind perceives and interprets visual data
  • Distinguish different types of visualizations and identify appropriate use cases
  • Evaluate visualizations’ interpretability based on experimental design
  • Apply data visualization methods using a reproducible workflow

Purpose of visualizations

  • Any kind of visual representation of information designed to enable communication, analysis, discovery, exploration, etc.
  • What to communicate
  • How to communicate

Information visualization

  • Information visualization
    • Scientific visualization
  • Abstract data
  • Data type
  • Goals of info viz

Information visualization

Statistical graphics

  • Visualize abstract data of a quantitative form
  • Goals

Scatterplot matricies

Scatterplot matrix of the Credit dataset. Source: An Introduction to Statistical Learning: With Applications in R.

Double-time bar charts

Double-time bar chart of crime in the city of San Francisco, 2009-10. Source: Visualizing Time with the Double-Time Bar Chart

Double-time bar charts

Double-time bar chart of crime in the city of San Francisco, 2009-10. Source: Visualizing Time with the Double-Time Bar Chart

Information dashboards

  • Business/industry
  • Lots of information
  • Extremely dense

Student performance

Dashboard for student performance. Source: 2012 Perceptual Edge Dashboard Design Competition: We Have a Winner!

Fitbit

Fitbit dashboard. Source: me

Infographics

  • Eye-catching
  • Quickly convey information
  • Not always accurate

Extremely sexual sun stroking. Source: The top 10 worst infographics ever created

Source: 11 Most Useless And Misleading Infographics On The Internet

Source: WTF Visualizations

Informative art

Dr. John Snow

Original map made by John Snow in 1854. Cholera cases are highlighted in black. Source: Wikipedia.

Charles Minard

Charles Minard’s 1869 chart showing the number of men in Napoleon’s 1812 Russian campaign army, their movements, as well as the temperature they encountered on the return path. Source: Wikipedia.

Minard’s map of Napoleon’s march on Russia

English translation of Minard’s map

NYTimes weather summaries

How Much Warmer Was Your City in 2015?

  • What data is related in the visualization? What are the dimensions/variables?
  • Approximately how many data points are recorded in the visualization?
  • What makes this a good/bad visualization?
  • What story is it conveying?

Basic data structures

  • Data type
  • Dataset type

Data types

Source: Visualization Analysis and Design. Tamara Munzner, with illustrations by Eamonn Maguire. A K Peters Visualization Series, CRC Press, 2014.

Dataset types

Source: Visualization Analysis and Design. Tamara Munzner, with illustrations by Eamonn Maguire. A K Peters Visualization Series, CRC Press, 2014.

Source: Visualization Analysis and Design. Tamara Munzner, with illustrations by Eamonn Maguire. A K Peters Visualization Series, CRC Press, 2014.

Tables

  • Flat table
    • Each row is an item
    • Each column is an attribute
    • Each cell is a value fully specified by the combination of row and column
  • Multidimensional table

Networks

A small example network with eight vertices and ten edges. Source: Wikipedia

Trees

Organization, mission, and functions manual: Civil Rights Division. Source: U.S. Department of Justice

Fields

Source: NASA Earth Observatory

Geometry

  • Shape of items with explicit spatial positions
  • 0D
  • 1D
  • 2D
  • 3D
  • Maps

Attribute types

Source: Visualization Analysis and Design. Tamara Munzner, with illustrations by Eamonn Maguire. A K Peters Visualization Series, CRC Press, 2014.

Semantics

  • Type vs. semantic
  • Key vs. value